Detail publikace

Bank-sourced credit transition matrices: Estimation and characteristics

Autor: Ing. Mgr. Barbora Štěpánková M.A., Ph.D.,
Typ: Články v impaktovaných časopisech
Rok: 2021
Číslo: 0
ISSN / ISBN: DOI: 10.1016/j.ejor.2020.06.024
Publikováno v: European Journal of Operational Research
Místo vydání:
Klíčová slova: Risk management, Credit risk, Transition matrices, Simulation, Banking
JEL kódy:
Granty: GAČR 18-05244S - Inovativní přístupy k řízení úvěrových rizik PRIMUS/19/HUM/17 2019-2021 Behaviorální finance a makroekonomie: Nové pohledy pro hlavní proud
Abstrakt: This study proposes and analyses a novel alternative to credit transition matrices (CTMs) developed by credit rating agencies - bank-sourced CTMs. It provides a unique insight into estimation of bank-sourced CTMs by assessing the extent to which the CTMs depend on the characteristics of the underlying credit risk datasets and the aggregation method and outlines that the choice of aggregation approach has a substantial effect on credit risk model results. Further, we show that bank-sourced CTMs are more dynamic than those of credit rating agencies, with higher off-diagonal transition rates and higher propensity to upgrade. Finally, we create a set of industry-specific CTMs, otherwise unobtainable due to the data sparsity faced by credit rating agencies, and highlight the implications of their differences, signalling the existence of industry-specific business cycles. The study uses a unique and large dataset of internal credit risk estimates from 24 global banks covering monthly observations on more than 26,000 large corporates and employs large-scale Monte Carlo simulations. This approach can be replicated by regulators (e.g., data collected by the European Central Bank in the AnaCredit project) and used by organisations aiming to improve their credit risk models.




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